Evidential Filtering and Spatio-Temporal Gradient for Micro-movements Analysis in the Context of Bedsores Prevention - IMT Mines Alès
Communication Dans Un Congrès Année : 2022

Evidential Filtering and Spatio-Temporal Gradient for Micro-movements Analysis in the Context of Bedsores Prevention

Résumé

In the context of pressure ulcer prevention, this article deals with the problem of detecting and analysing micro-movements in the sacral area of bedridden patients on mattresses equipped with a network of pressure sensors. The study is based on a series of pressure measurements carried out on a cohort of patients lying on two types of mattress at the Nîmes university hospital (France). A spatio-temporal model considers first the local information of measurements from the array of sensors using an evidential filter in order to remove spatial uncertainties or measurement noise before micro-movement analysis. With a Detrended Fluctuation Analysis (DFA), the complexity level of the time series coming from the micro-movement model is finally estimated for different noise filters.
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Dates et versions

hal-03800992 , version 1 (06-10-2022)

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Citer

Nicolas Sutton-Charani, Francis Faux, Didier Delignières, Willy Fagard, Arnaud Dupeyron, et al.. Evidential Filtering and Spatio-Temporal Gradient for Micro-movements Analysis in the Context of Bedsores Prevention. BELIEF 2022 - 7th International Conference on Belief Functions, Oct 2022, Paris, France. pp.297-306, ⟨10.1007/978-3-031-17801-6_28⟩. ⟨hal-03800992⟩
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